Quantum Algorithms and Quantum Machine Learning
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 54
Special Issue Editor
Special Issue Information
Dear Colleagues,
Quantum computing promises to fundamentally transform the way complex computational problems are formulated and solved. With rapid advances in quantum hardware and increasing access to noisy intermediate-scale quantum (NISQ) devices, the design of efficient quantum algorithms and the understanding of their computational complexity have become central topics in quantum information science. At the same time, quantum machine learning has emerged as a promising interdisciplinary area, aiming to combine the expressive power of quantum systems with data-driven learning paradigms.
This Special Issue focuses on recent theoretical and practical developments in quantum algorithms, quantum complexity, and quantum machine learning. It aims to provide a forum for high-quality contributions addressing algorithmic design, complexity analysis, and implementation-oriented optimization techniques. Topics of interest include, but are not limited to, quantum algorithmic frameworks, quantum learning models, quantum circuit optimization and design automation, quantum finite automata, and complexity-theoretic aspects of quantum computation. Particular attention is also given to resource-efficient methods suitable for NISQ-era devices, as well as rigorous analyses that deepen our understanding of quantum advantage.
By bringing together researchers from quantum computing, theoretical computer science, and machine learning, this Special Issue seeks to highlight emerging trends, identify open challenges, and stimulate cross-disciplinary collaboration. We welcome original research articles, reviews, and perspectives that advance the foundations and applications of quantum algorithms and quantum machine learning.
Dr. Shenggen Zheng
Guest Editor
Manuscript Submission Information
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Keywords
- quantum algorithms
- quantum computational complexity
- quantum machine learning
- quantum circuit optimization
- quantum circuit design automation
- NISQ algorithms
- variational quantum algorithms
- quantum finite automata
- quantum information processing
- resource-efficient quantum computation
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